The dataset contains information of Diameter at Breast Height (DBH) of 8,729 trees. These trees are distributed in 29 RAINFOR network forest plots across the Brazilian Amazon, comprising the states of Acre, Mato Grosso and Pará. All the plot censuses are located in terra-firme non-flooded lowland forests. The measurements were collected between 2017 and 2019. The Amazon Forest Inventory Network is a long-term, international collaboration to understand the dynamics of Amazon ecosystems. Since 2000 they have developed a framework for systematic monitoring of forests from the ground-up, centred on plots that track the fate of trees and species, and includes soil and plant biogeochemical records, as well as intensive monitoring of carbon cycle processes at some sites. RAINFOR works with partners across the nations of Amazonia to support and sustain forest monitoring and help develop new generations of Amazon ecologists. The work of RAINFOR is currently supported by funding agencies in Brazil, the UK, and the EU. Full details about this dataset can be found at https://doi.org/10.5285/63d4b774-4e03-4db2-95ad-dcca18f0d681

This dataset consists of structure, biomass (carbon density) and biodiversity (plant species richness) from forest inventory plots at forest restoration sites in South and Southeast Asia and the code for the analyses of these data as conducted in Banin, Raine et al (2023). The recorded data consists of plot level censuses carried out up to May 2021 collated from published studies, grey literature and data provided by co-authors. This represents the collation of data from 11 sites in areas where disturbance had led to the clearance or degradation of natural forest. Plots where tree seedlings were planted (active restoration) and plots where no seedling planting took place (natural regeneration) were censused for structure, biomass and/or biodiversity. Some of the sites in the dataset also recorded data at old growth forest plots for reference, and/or provided repeat measures of forest metrics over time. The dataset also includes the code used for analysis of this plot level data, used to compare the outcome of different restoration approaches. Full details about this dataset can be found at https://doi.org/10.5285/3d3b1d09-9e7a-4144-b8a1-b09a3c573466